We build AI for organizations that work with complex documents.

Cogniterm brings together document understanding, language models, and data protection to help enterprises and public institutions apply AI to everyday work.

Useful in practice. Designed for your operating requirements.

We start with the work: the documents people use, the decisions they support, and the requirements that shape how systems are deployed and managed.

All-in-one suite

Integrated AI capabilities

  • Document processing with AI OCR and image preprocessing
  • Management and evaluation of prompts and RAG components, with content filtering
  • Vector database operations, a generative AI portal, and agent orchestration

Domain analysis

Domain-specific implementation

  • Requirements analysis from an ERP and process redesign perspective (BPR/BPA)
  • Domain schemas, knowledge graphs, and policy rules that reflect how the work is organized
  • Task-specific evaluation criteria, including accuracy, recall, answer grounding, and operational metrics

Delivery

Deployment and ongoing operations

  • Project experience from on-site PoC to pilot to organization-wide rollout
  • Support for authentication, auditing, access control, and logging requirements
  • On-premises, VPC, and hybrid deployments that connect to existing systems

The expertise to take AI
from a use case to daily use

Five teams cover each stage of the work, from consulting and model development to platform engineering, product planning, and customer partnerships.

  1. AI consulting

    Define the use case, implementation roadmap, and evaluation criteria.

    We analyze how work moves through your organization and propose an AI transformation (AX) strategy, from LLM fine-tuning to RAG design. We plan adoption roadmaps and governance, and run PoCs and pilots in clearly defined stages.

  2. AI model development

    Develop and evaluate models for document recognition, classification, and domain-specific tasks.

    We research and develop models that balance accuracy and cost. Training, tuning, quantization, and A/B testing help us improve capabilities such as OCR, contextual classification, and image recognition. Model cards and data sheets document how each model was built and evaluated.

  3. AI architecture and R&D

    Design the infrastructure, integrations, and operations needed to run AI systems.

    Our architecture team and corporate R&D center build the platform behind our AI products. The work covers infrastructure for multi-cloud and on-premises environments, LLMOps, MLOps, and monitoring, along with agent orchestration and inference optimization.

  4. Product planning

    Turn technical capabilities into products and workflows people can use.

    We are responsible for productization, from product strategy and UX to pricing and packaging. Quality standards, test processes, and interface design start from the customer experience and continue after launch.

  5. Business and partnerships

    Connect customer requirements with the right solutions and delivery partners.

    We lead sales, proposals, and partnerships. Working with customers in each industry, we gather feedback after deployment and use it to plan support and expansion.

Generative AI for enterprise work,
in one place

We provide an AI environment designed to connect with your existing infrastructure.
Start with the services you need, then expand as your requirements grow.

Enterprise Gen AI SaaS

  • Private cloud, on-premises, and hybrid environments
  • Generative AI guardrails for policy-based controls
  • No-code RAG for faster setup
  • Built-in AI security and data protection controls

AI model development and automation

  • Domain-specific LLM development and fine-tuning
  • Multimodal AI model development (text, image, speech)
  • Operations automation with AIOps and LLMOps
  • Unstructured data processing and automation with AI OCR
  • Industry-specific algorithm design and optimization

Our progress

Milestones in our product development and work with customers.

  1. 2026

    • Won the Korean National Police Agency AI OCR project
    • Signed an AI solution supply contract for the Ministry of Finance and Economy (MOFE) AI-One platform
    • Certified as a venture company
    • Signed a contract to supply a legal LLM and AI search engine to the Korea Institute of Local Finance (KILF)
    • Signed phase 2 of the Tax Tribunal public-sector AI transformation (AX) project for tax appeals and review
  2. 2025

    Commercialization phase 2

    • Delivered a generative AI solution to Gwangju City (Gyeonggi Province)
    • Selected as one of six finalist startups in the Jeju Center for Creative Economy & Innovation AI Open Ground program
    • Signed phase 1 of the Tax Tribunal public-sector AI transformation (AX) project for tax appeals and review
    • Selected as a Super-Gap Startup (LLM) and ran an AI agent PoC with KT
    • Established the Cogniterm Corporate R&D Center
    • Built a generative AI PoC for the Ministry of Economy and Finance (MOEF)
  3. 2021–2024

    Commercialization phase 1

    • Built natural language and image deep learning models
    • Took part in developing AI labeling tools and AI models
  4. 2021

    Founded

    • Company incorporated